Small data, thick data : Thickening strategies for trace-based social media research
Latzko-Toth, Guillaume, Claudine Bonneau et Mélanie Millette. 2017. Small data, thick data : Thickening strategies for trace-based social media research. Dans Anabel Quan-Haase et Luke Sloan (dirs.) The SAGE Handbook of Social Media Research Methods. Londres : SAGE, 199-214.
The algorithmic processing of very large sets of ‘traces’ of user activities collected by digital platforms – so-called ‘Big Data’ – exerts a strong appeal on social media researchers. In the context of a computational turn in social sciences and humanities, is qualitative research based on small samples and corpuses (‘small data’) still relevant? It is argued that the unique value of such research lies in data thickness. This is achieved through a process we call thickening. Drawing on recent case studies in social media research we have conducted, we propose and illustrate three strategies to thicken trace data: trace interview, manual data collection and agile long-term online observation.
Ce contenu a été mis à jour le 26 octobre 2018 à 22 h 09 min.